Statistical analysis and optimization of mercury removal from aqueous solution onto green synthesized magnetite nanoparticle using central composite design

The present study mainly focuses on the statistical analysis and optimization of Hg(II) removal from aqueous solution by wheat straw-supported magnetite nanoparticles (Fe₃O₄-WSS NPs). A response surface methodology with the central composite design was used to optimize the adsorption of Hg(II) and adsorption parameters. Following a central composite design (CCD) model, the result of the analysis revealed that the optimum adsorption parameters acquired by the quadratic model for maximum percentage removal of Hg(II) were 6.42, 40 mg/L, 1 g, and 35 min for pH, initial Hg(II) concentration, the dosage of wheat straw-supported magnetite nanoparticles, and contact time respectively. Under these conditions, the maximum removal efficiency of Hg(II) was found to be 98.60%. Langmuir isotherm model yielded the best fit to the experimental data with a maximum adsorption capacity of 112.40 mg/g. The results from the kinetic study also showed that the pseudo-second-order model well predicted the adsorption process. Moreover, the findings of the studies were predominantly fitted to a pseudo-second kinetic model, the Elovich kinetic model, and the Dubinin-Radushkevich isotherm model indicating that the rate-limiting step for the adsorption of Hg(II) ions onto Fe₃O₄-WSS NPs was of chemisorption processes. The results from thermodynamic parameters (∆H^o, ∆G^o, ∆S^o) indicated that the removal process of Hg(II) ions was endothermic, spontaneous, and feasible. The study performed for the regeneration and reusability cycles showed wheat straw-supported magnetite nanoparticles can retain more than 86% of Hg(II) ions over the five cycles.